A New Linear Regression Kalman Filter with Symmetric Samples
Nonlinear filtering is of great significance in industries. In this work, we develop a new linear regression Kalman filter for discrete nonlinear filtering problems. Under the framework of linear regression Kalman filter, the key step is minimizing the Kullback–Leibler divergence between standard no...
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Autores principales: | Xiuqiong Chen, Jiayi Kang, Mina Teicher, Stephen S.-T. Yau |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
MDPI AG
2021
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Materias: | |
Acceso en línea: | https://doaj.org/article/91b554243a86435383eb991227c7f9c4 |
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